{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# ***Introduction to Radar Using Python and MATLAB***\n",
    "## Andy Harrison - Copyright (C) 2019 Artech House\n",
    "<br/>\n",
    "\n",
    "# Bistatic Radar Range Equation\n",
    "***"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The output signal to noise ratio for a bistatic radar configuration is given by (Equation 4.61)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\\begin{equation}\\label{eq:bistatic_snr_output}\n",
    "    {SNR}_o = \\frac{P_t\\, G_t(\\theta, \\phi)\\, G_r(\\theta, \\phi)\\, \\sigma(\\theta, \\phi)\\, \\lambda^2}{(4\\pi)^3\\,k\\,T_0\\,B\\,F L_t\\, L_r\\,r_t^2\\,r_r^2}\n",
    "\\end{equation}\n",
    "***"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Begin by getting the library path"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import lib_path"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Set the minimum and maximum range product (m)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "range_product_min = 1e6\n",
    "\n",
    "range_product_max = 1e9"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Import the `linspace` routine from `scipy`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "from numpy import linspace"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Set up the range product array"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "range_product = linspace(range_product_min, range_product_max, 2000)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Set the noise figure (dB), transmit losses (dB), receive losses (dB), transmit antenna gain (dB), receive antenna gain (dB), and the bistatic target RCS (dBsm)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "noise_figure = 3.0\n",
    "\n",
    "transmit_losses = 9.0\n",
    "\n",
    "receive_losses = 6.0\n",
    "\n",
    "transmit_antenna_gain = 25.0\n",
    "\n",
    "receive_antenna_gain = 30.0\n",
    "\n",
    "bistatic_target_rcs = -10.0"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Set the system temperature (K), the bandwidth (Hz), the transmit peak power (W), and the operating frequency (Hz)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "system_temperature = 290\n",
    "\n",
    "bandwidth = 1e6\n",
    "\n",
    "peak_power = 50e3\n",
    "\n",
    "frequency = 1e9"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Set up the input args"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "kwargs = {'transmit_target_range': 1.0,\n",
    "\n",
    "          'receive_target_range': range_product,\n",
    "\n",
    "          'system_temperature': system_temperature,\n",
    "\n",
    "          'bandwidth': bandwidth,\n",
    "\n",
    "          'noise_factor': 10 ** (noise_figure / 10.0),\n",
    "\n",
    "          'transmit_losses': 10 ** (transmit_losses / 10.0),\n",
    "\n",
    "          'receive_losses': 10 ** (receive_losses / 10.0),\n",
    "\n",
    "          'peak_power': peak_power,\n",
    "\n",
    "          'transmit_antenna_gain': 10 ** (transmit_antenna_gain / 10.0),\n",
    "\n",
    "          'receive_antenna_gain': 10 ** (receive_antenna_gain / 10.0),\n",
    "\n",
    "          'frequency': frequency,\n",
    "          \n",
    "          'bistatic_target_rcs': 10 ** (bistatic_target_rcs / 10.0)}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Import the `output_snr` routine from `bistatic_radar_range`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "from Libs.radar_range.bistatic_radar_range import output_snr"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Calculate the bistatic output signal to noise ratio"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "output_snr = output_snr(**kwargs)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Import the `matplotlib` routines and `log10` from `scipy` for displaying the results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "from matplotlib import pyplot as plt\n",
    "\n",
    "from numpy import log10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Set the figure size\n",
    "\n",
    "plt.rcParams[\"figure.figsize\"] = (15, 10)\n",
    "\n",
    "\n",
    "# Display the results\n",
    "\n",
    "plt.plot(range_product / 1.0e6, 10.0 * log10(output_snr), '')\n",
    "\n",
    "\n",
    "# Set the plot title and labels\n",
    "\n",
    "plt.title('Bistatic Output Signal to Noise Ratio', size=14)\n",
    "\n",
    "plt.xlabel('Range Product (km$^2$)', size=12)\n",
    "\n",
    "plt.ylabel('Output Signal to Noise Ratio (dB)', size=12)\n",
    "\n",
    "\n",
    "# Set the tick label size\n",
    "\n",
    "plt.tick_params(labelsize=12)\n",
    "\n",
    "\n",
    "# Turn on the grid\n",
    "\n",
    "plt.grid(linestyle=':', linewidth=0.5)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
